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Some medications taken by the breastfeeding women are excreted into milk, posing a potential risk of toxicity to the infant. The first line of evidence required for toxicity risk assessment is prediction of drug levels in milk. However, pharmacokinetic (PK) information of drug excretion into milk is largely lacking, or limited to data from case reports. This makes it difficult to provide population-level prediction of drug levels in milk. The lack of data on this topic jeopardizes not only maternal adherence to drug therapy during breastfeeding but also establishment of breastfeeding, even if the drug is considered safe during nursing. Clearly, this clinical problem in drug safety is an important women's health issue, affecting both mother and infant. "Drugs in Lactation" Analysis Consortium (DLAC) is a "drug-in-milk" monitoring network, which is designed as a platform for efficient collection of patient milk samples in a real world setting to generate population predictions of drug excretion levels into human milk.
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OVERARCHING GOAL OF DLAC:
To establish a post-marketing "drug-in-milk" monitoring system for nursing women who are prescribed and using medications. Drugs in Lactation Analysis Consortium (DLAC) will provide risk assessment data and tools for toxicity detection in the form of population estimates and variations of drug levels in mother's milk and infant plasma for several common medications in a real world setting.
SPECIFIC OBJECTIVES:
SCOPE AND RATIONALE:
Information on the extent of drug excretion into mother's milk is lacking, mainly due to the following two reasons: 1) nursing women are excluded from drug trials; 2) ethical and practical difficulties in conducting intensive-sampling PK studies in the breastfeeding mothers. Even if data exist, they are based on small numbers of patients, and it is difficult to translate the information into population estimates of drug levels in milk. DLAC is developed as a novel drug safety network using population PK (popPK) modeling approach, which allows population-level PK parameter estimation, modeling and simulation based on a scheme of sparse sampling per individual, systematically collected from a large number of nursing women on medication in real world setting. This approach will provide population risk estimates as probability distribution of reaching certain drug level in milk and plasma. Equipped with a versatile drug analysis core and a popPK modeling and simulation unit, DLAC will be able to generate PK estimates of a population in the context of breastfeeding.
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68 participants in 1 patient group
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Data sourced from clinicaltrials.gov
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